read_srm_export <- function(filename, columns = c("peak_name", "RT.min", "basepeak", "area.cpm", "height.cts", "quantitation")) {
filename %>%
# read excel files
read_excel(sheet = "Integration", skip = 42,
col_names = columns, col_types = rep("text", length(columns))) %>%
as_data_frame() %>%
# remove empty rows
filter(!is.na(peak_name), peak_name != "n.a.") %>%
# convert the relevant numeric columns into numbers
mutate_at(vars(RT.min, area.cpm, height.cts), as.numeric) %>%
# remove useless columns
select(-basepeak, -quantitation) %>%
# add filename info
mutate(file_id = gsub("\\.xls", "", basename(filename))) %>%
select(file_id, everything())
}
# get data
all_data <-
# find all excel files ##change name and use new folder for new project
list.files( "data_SH1", recursive = TRUE, full.names = TRUE, pattern = "\\.xls$") %>%
# send them to the read method
lapply(read_srm_export) %>%
# combine the data set
bind_rows() %>%
# pull out sample information
#mutate(sample_id = str_match(all_data$file_id, "TSQ\\d+_GB_(.*)$") %>% { .[,2] }) %>%
# get n replicates
group_by(file_id)
#mutate(n_replicates = length(unique(file_id)))
depth_and_rock_info <- read_excel(file.path("metadata", "aliphaticSRM_SH1.xlsx")) %>%
rename(tle = `TLE.mg`, maltene = `maltenes.mg`, ref_amount_added.ug = `D4.ug` )%>%
filter(!is.na(file_id)) %>%
filter (process == "yes")
depth_and_rock_info
data_by_depth <-
all_data %>%
left_join(depth_and_rock_info, by = "file_id") %>%
group_by(file_id) %>%
mutate(
n_peaks = n(),
n_standards = sum(peak_name == "D4 C29 ISTD"),
ref_area.cpm = area.cpm[peak_name == "D4 C29 ISTD"],
amount.ug = area.cpm/ref_area.cpm * ref_amount_added.ug,
#Normalize by what you want
conc_rock.ug_g = amount.ug / rock.g,
conc_tle.ug.g = amount.ug / tle,
conc_maltene.ug.g = amount.ug / maltene
)%>% ungroup() %>%
arrange(file_id, peak_name)
data_by_depth
standard <- read_excel(file.path("metadata", "D4_calibration.xlsx")) ###read excel
###calibration curve
standard %>%
ggplot() +
aes(x = Known.ng, y = Measured_area.counts, color = calibration) +
geom_smooth(method = "lm", alpha = 0.5) +
geom_point() +
theme_bw() +
theme(legend.position = "none")
calibrations <-
standard %>%
filter(!is.na(calibration)) %>%
nest(-calibration) %>%
mutate(
fit = map(data, ~summary(lm(`Measured_area.counts`~ `Known.ng`, data = .x))),
coefficients = map(fit, "coefficients"),
intercept = map_dbl(coefficients, `[`, 1, 1),
intercept_se = map_dbl(coefficients, `[`, 1, 2),
slope = map_dbl(coefficients, `[`, 2, 1),
slope_se = map_dbl(coefficients, `[`, 2, 2),
r2 = map_dbl(fit, "r.squared")
)
calibrations %>% select(-data, -fit, -coefficients) %>% knitr::kable(d = 3)
| calibration | intercept | intercept_se | slope | slope_se | r2 |
|---|---|---|---|---|---|
| jan2018 | 705.862 | 1371.146 | 72929.67 | 3337.256 | 0.996 |
These numbers are not useful for anything else.
calib_data <-
data_by_depth %>%
# temp
mutate(calibration = "jan2018") %>%
left_join(calibrations, by = "calibration") %>%
mutate(
total_volume.uL = 100,
total_inject.uL = 1.5,
ref_amount_inject_expected.ng = (ref_amount_added.ug * 1000)/total_volume.uL * total_inject.uL ,
ref_amount_inject_measured.ng = (ref_area.cpm - intercept)/slope,
ref_amount_measured.ug = ((total_volume.uL* ref_amount_inject_measured.ng)/total_inject.uL) * 1/1000,
yield = (ref_amount_inject_measured.ng/ref_amount_inject_expected.ng) * 100
)
calib_data
sum_peaks <- function(df, filter_condition, new_peak_name) {
filter_condition <- sprintf("(%s)", str_c(filter_condition, collapse = "|"))
filter(df, str_detect(peak_name, filter_condition)) %>%
summarize(
file_id = file_id[1],
depth = depth[1],
conc_rock.ug_g = sum(conc_rock.ug_g)
) %>%
mutate(peak_name = new_peak_name)
}
ratio_peaks <- function(df, filter_top, filter_bottom, new_peak_name) {
filter_top <- sprintf("(%s)", str_c(filter_top, collapse = "|"))
filter_bottom <- sprintf("(%s)", str_c(filter_bottom, collapse = "|"))
filter(df, str_detect(peak_name, filter_top) | str_detect(peak_name, filter_bottom)) %>%
summarize(
file_id = file_id[1],
depth = depth[1],
ratio = sum(conc_rock.ug_g[str_detect(peak_name, filter_top)]) / sum(conc_rock.ug_g[str_detect(peak_name, filter_bottom)])
) %>%
mutate(peak_name = new_peak_name)
}
#set values to use for later calculations
final_data1 <- calib_data %>%
group_by(file_id) %>%
do({
bind_rows(.,
#C27_Dia/Reg
sum_peaks(., c("C27 aB 20R ST", "C27 aB 20S ST"), "C27Dia"),
sum_peaks(., c("C27 aaa 20R ST", "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C27 Ba 20R ST", "C27 Ba 20S ST"), "C27Reg"),
#Total Tricyclics
sum_peaks(., c("C19 Tri HO", "C20 Tri HO", "C21 Tri HO", "C22 Tri HO", "C23 Tri HO", "C24 Tet HO", "C24 Tri HO", "C25 Tri R+S HO", "C26 Tri R HO", "C26 Tri S HO"), "all_tricyclics"),
#4Me_TriMe
sum_peaks(., c("4B Me 5a cholestane", "4B Me 24 ethyl 5a cholestane", "4B,23S,24S trimethyl 5a cholestane", "4B,23S,24R trimethyl 5a cholestane", "4B,23R,24S trimethyl 5a cholestane", "4B,23R,24R trimethyl 5a cholestane", "4a Me 5a cholestane", "4a Me 24 ethyl 5a cholestane", "4a,23S,24S trimethyl 5a cholestane", "4a,23S,24R trimethyl 5a cholestane", "4a,23R,24S trimethyl 5a cholestane", "4a,23R,24R trimethyl 5a cholestane"), "4Me_TriMe"),
#allRegSt
sum_peaks(., c("C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST","C27 aBB 20S ST", "C27 aBB 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST","C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aBB 20 R+S ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "allRegst"),
#C26St
sum_peaks(., c("C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST"), "C26Regst"),
#C27St
sum_peaks(., c("C27 aBB 20S ST", "C27 aBB 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST"), "C27Regst"),
#C28St
sum_peaks(., c("C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST"), "C28Regst"),
#C29St
sum_peaks(., c("C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST"), "C29Regst"),
#C30St
sum_peaks(., c("C30 aBB 20 R+S ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "C30Regst"),
#allRegHO
sum_peaks(., c("Ts C27 HO", "Tm C27 HO", "C27 17B H Ho", "29, 30 C28H bisnor HO", "28, 30 C28 bisnor HO", "C29 Ts HO", "C29 Ba HO", "C29 BB Ho", "C30 aB HO", "C30 BB HO", "C30H Ba HO", "C31 HR Ba HO", "C31 aB HR HO", "C31 aB HS HO", "C31 BB HO", "C32 aB HS HO", "C32 aB HR HO", "C33 aB HS HO", "C33 aB HR HO", "C34 aB HR HO", "C34 aB HS HO", "C35 aB HR HO", "C35 aB HS HO"), "allRegHO") ,
#allDiacholestane
sum_peaks(., c("20S, 4a Me 13B,17a,H diacholestane", "20R, 4a Me 13B,17a,H diacholestane" , "20R, 4a Me 13a,17B,H diacholestane", "20S, 4a,24 dimethyl 13B,17a,H diacholestane", "20R 4a,24 dimethyl 13B,17a,H diacholestane", "20R, 4a,24 dimethyl 13a,17B,H diacholestane" , "20S, 4a,24 dimethyl 13a,17B,H diacholestane", "4a,24 dimethyl 5a cholestane" , "4B,24 dimethyl 5a cholestane"), "allDiacholestane"),
#all Steranes
sum_peaks(., c("C26 Ba 20S ST", "C26 Ba 20R ST", "C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20R ST", "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C27 Ba 20R ST", "C27 Ba 20S ST", "C28 Ba 20S ST", "C28 Ba 20R ST", "C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST" , "C29 Ba 20S ST", "C29 Ba 20R ST", "C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST" , "C30 Ba 20S ST", "C30 Ba 20R ST", "C30 aBB 20(R+S) ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "C30 4a Me 20S ST", "C30 4a Me 20R ST + DINO st", "C30 3B Me BB 20S ST", "C30 3B Me 20S ST + C30 3B Me BB 20R ST" , "C30 3BMe 20R ST", "C30 2aMe 20S ST", "C30 2a Me 20R + 4a Me BB 20S ST" , "4B Me 5a cholestane", "4B Me 24 ethyl 5a cholestane", "4B,23S,24S trimethyl 5a cholestane", "4B,23S,24R trimethyl 5a cholestane", "4B,23R,24S trimethyl 5a cholestane", "4B,23R,24R trimethyl 5a cholestane", "4a Me 5a cholestane", "4a Me 24 ethyl 5a cholestane", "4a,23S,24S trimethyl 5a cholestane", "4a,23S,24R trimethyl 5a cholestane", "4a,23R,24S trimethyl 5a cholestane", "4a,23R,24R trimethyl 5a cholestane", "20S, 4a Me 13B,17a,H diacholestane", "20R, 4a Me 13B,17a,H diacholestane" , "20R, 4a Me 13a,17B,H diacholestane", "20S, 4a,24 dimethyl 13B,17a,H diacholestane", "20R 4a,24 dimethyl 13B,17a,H diacholestane", "20R, 4a,24 dimethyl 13a,17B,H diacholestane" , "20S, 4a,24 dimethyl 13a,17B,H diacholestane", "4a,24 dimethyl 5a cholestane" , "4B,24 dimethyl 5a cholestane"), "allSteranes"),
#everything
sum_peaks(., c(""), "everything"),
#2 Me Hopanes
sum_peaks(., c("C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), "2MeHo_all"),
#3 Me Hopanes
sum_peaks(., c("C31 3B Me HO", "C32 3B Me S HO", "C32 3B Me R HO", "C32 3B Me Ba 22S+R ST", "C33 3BMe S HO", "C33 3BMe R HO", "C34 3B Me S Ho", "C34 3B Me R HO", "C35 3B Me R HO", "C35 3B Me S HO", "C36 3B Me S HO", "C36 3B Me R HO"), "3MeHo_all")
) }) %>% ungroup()
final_data <- final_data1 %>%
group_by(file_id) %>%
do({
bind_rows(.,
#Source
#C19/tricyclics
ratio_peaks(., "C19 Tri HO", "all_tricyclics", "C19/tricyclics"),
#C20/tricyclics
ratio_peaks(., "C20 Tri HO", "all_tricyclics", "C20/tricyclics"),
#C21/tricyclics
ratio_peaks(., "C21 Tri HO", "all_tricyclics", "C21/tricyclics"),
#C22/tricyclics
ratio_peaks(., "C22 Tri HO", "all_tricyclics", "C22/tricyclics"),
#C23/tricyclics
ratio_peaks(., "C23 Tri HO", "all_tricyclics", "C23/tricyclics"),
#C24/tricyclics
ratio_peaks(., c("C24 Tet HO", "C24 Tri HO"), "all_tricyclics", "C24/tricyclics"),
#C24TET/tricyclics
ratio_peaks(., "C24 Tet HO", "all_tricyclics", "C24tet/tricyclics"),
#C25/tricyclics
ratio_peaks(., "C25 Tri R+S HO", "all_tricyclics", "C25/tricyclics"),
#C26/tricyclics
ratio_peaks(., c("C26 Tri R HO", "C26 Tri S HO"), "all_tricyclics", "C26/tricyclics"),
#tricyclics/all
ratio_peaks(., "all_tricyclics", c(""), "tricyclics/all"),
#C19/C19+23
ratio_peaks(., "C19 Tri HO", c("C19 Tri HO", "C23 Tri HO"), "C19/C19+23"),
#C20/C20+23
ratio_peaks(., "C20 Tri HO", c("C20 Tri HO", "C23 Tri HO"), "C20/C20+23"),
#Ho/St
ratio_peaks(., "allRegHO", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "Ho/St"),
#Ho/St%
ratio_peaks(., "allRegHO", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "allRegHO" ), "Ho/St%"),
#C31_2MHI
ratio_peaks(., "C31 2a Me Ho", c("C30 aB HO", "C31 2a Me Ho" ), "C31_2MHI"),
#C31_35_2MHI
ratio_peaks(., c("C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), c("C30 aB HO", "C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), "C31_35_2MHI"),
#C31_2-MHI/C27-C30Steranes
ratio_peaks(., "C31 2a Me Ho", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST" ,"C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "C31 2a Me Ho" ), "C31_2-MHI/C27-C30Steranes"),
#C31 3-MHI
ratio_peaks(., "C31 3B Me HO", c("C31 3B Me HO", "C30 aB HO"), "C31 3-MHI"),
#C31_35_3MHI(%)
ratio_peaks(., c("C31 3B Me HO", "C32 3B Me S HO", "C32 3B Me R HO", "C32 3B Me Ba 22S+R ST", "C33 3BMe S HO", "C33 3BMe R HO", "C34 3B Me S Ho", "C34 3B Me R HO", "C35 3B Me R HO", "C35 3B Me S HO", "C36 3B Me S HO", "C36 3B Me R HO"), c("C30 aB HO","C31 3B Me HO", "C32 3B Me S HO", "C32 3B Me R HO", "C32 3B Me Ba 22S+R ST", "C33 3BMe S HO", "C33 3BMe R HO", "C34 3B Me S HO", "C34 3B Me R HO", "C35 3B Me R HO", "C35 3B Me S HO", "C36 3B Me S HO", "C36 3B Me R HO" ) ,"C31_35_3MHI(%)"),
#C29ab/C29ab+C30ab
ratio_peaks(., "C29 aB HO", c( "C29 aB HO" , "C30 aB HO"), "C29ab/C29ab+C30ab"),
#C29ab/allHoab
ratio_peaks(., "C29 aB HO" , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C29ab/allHoab"),
#C30ab/allHoab
ratio_peaks(., "C30 aB HO" , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C30ab/allHoab"),
#C31ab/allHoab
ratio_peaks(., c("C31 aB HS HO", "C31 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C31ab/allHoab"),
#C32ab/allHoab
ratio_peaks(., c("C32 aB HR HO", "C32 aB HS HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C32ab/allHoab"),
#C33ab/allHoab
ratio_peaks(., c( "C33 aB HS HO" , "C33 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C33ab/allHoab"),
#C34ab/allHoab
ratio_peaks(., c( "C34 aB HS HO", "C34 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C34ab/allHoab"),
#C35ab/allHoab
ratio_peaks(., c("C35 aB HS HO", "C35 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C35ab/allHoab"),
#OleananeIndex
ratio_peaks(., "Oleanane HO", c("Oleanane HO", "C30 aB HO"), "OleananeIndex"),
#HHI
ratio_peaks(., c("C35 aB HS HO", "C35 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO"), "HHI"),
#C35/C35+C34
ratio_peaks(., c("C35 aB HS HO", "C35 aB HR HO"), c("C34 aB HS HO", "C34 aB HR HO","C35 aB HS HO", "C35 aB HR HO"), "C35/C35+C34"),
#GI
ratio_peaks(., "gamma", c("gamma", "C30 aB HO"), "GI"),
#28,30BNH/28,30BNH+C30
ratio_peaks(., "28, 30 C28 bisnor HO", c("28, 30 C28 bisnor HO", "C30 aB HO"), "28,30BNH/28,30BNH+C30") ,
#Source
#C26St/allSt ##INCLUDES ME's
ratio_peaks(., c("C26 Ba 20S ST", "C26 Ba 20R ST", "C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST"), "allSteranes", "C26St/allSt"),
#C27St/allSt
ratio_peaks(., c("C27 aaa 20R ST", "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C27 Ba 20R ST", "C27 Ba 20S ST"), "allSteranes", "C27St/allSt"),
#C28St/allSt
ratio_peaks(., c("C28 Ba 20S ST", "C28 Ba 20R ST", "C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST"), "allSteranes", "C28St/allSt"),
#C29St/allSt
ratio_peaks(., c("C29 Ba 20S ST", "C29 Ba 20R ST", "C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST"), "allSteranes", "C29St/allSt"),
#C30St/allSt (does not include Me's in numerator)
ratio_peaks(., c("C30 Ba 20S ST", "C30 Ba 20R ST", "C30 aBB 20(R+S) ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "allSteranes", "C30St/allSt"),
#C30Me/allSt (C30 Me's in numerator)(not in MRM spreadsheet)
ratio_peaks(., c("C30 4a Me 20S ST", "C30 4a Me 20R ST + DINO st", "C30 3B Me BB 20S ST", "C30 3B Me 20S ST + C30 3B Me BB 20R ST", "C30 3BMe 20R ST", "C30 2aMe 20S ST", "C30 2a Me 20R + 4a Me BB 20S ST"), "allSteranes", "C30Me/allSt"),
#DinoSt/allSt
ratio_peaks(., c("4B Me 5a cholestane", "4B Me 24 ethyl 5a cholestane", "4B,23S,24S trimethyl 5a cholestane", "4B,23S,24R trimethyl 5a cholestane", "4B,23R,24S trimethyl 5a cholestane", "4B,23R,24R trimethyl 5a cholestane", "4a Me 5a cholestane", "4a Me 24 ethyl 5a cholestane", "4a,23S,24S trimethyl 5a cholestane", "4a,23S,24R trimethyl 5a cholestane", "4a,23R,24S trimethyl 5a cholestane", "4a,23R,24R trimethyl 5a cholestane"), "allSteranes", "DinoSt/allSt"),
#C26/(C26-30)aaaSR
ratio_peaks(., c("C26 aaa 20R ST", "C26 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C26/(C26-30)aaaSR"),
#C27/(C26-30)aaaSR
ratio_peaks(., c("C27 aaa 20R ST", "C27 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C27/(C26-30)aaaSR"),
#C28/(C26-30)aaaSR
ratio_peaks(., c("C28 aaa 20R ST", "C28 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C28/(C26-30)aaaSR"),
#C29/(C26-30)aaaSR
ratio_peaks(., c("C29 aaa 20R ST", "C29 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C29/(C26-30)aaaSR"),
#C30/(C26-30)aaaSR
ratio_peaks(., c("C30 aaa 20R ST", "C30 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C30/(C26-30)aaaSR"),
#C27/C27+C28aaa&abb
ratio_peaks(., c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST"), c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST") , "C27/C27+C28aaa&abb"),
#C27/C27+C29aaa&abb
ratio_peaks(., c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST"), c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST") , "C27/C27+C29aaa&abb"),
#C28/C28+C27aaa&abb
ratio_peaks(., c("C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST"), c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST") , "C28/C28+C27aaa&abb"),
#C28/C28+C29aaa&abb
ratio_peaks(., c("C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST"), c("C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST", "C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST") , "C28/C28+C29aaa&abb"),
#C29/C29+C27aaa&abb
ratio_peaks(., c("C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST"), c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST") , "C29/C29+C27aaa&abb"),
#C29/C29+C28aaa&abb
ratio_peaks(., c("C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST"), c("C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST", "C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST") , "C29/C29+C28aaa&abb"),
#4Me_TriMe/Me_C26St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST") , "4Me_TriMe/Me_C26St"),
#4Me_TriMe/Me_C27St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C27 aBB 20S ST", "C27 aBB 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST") , "4Me_TriMe/Me_C27St"),
#4Me_TriMe/Me_C28St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST") , "4Me_TriMe/Me_C28St"),
#4Me_TriMe/Me_C29St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST") , "4Me_TriMe/Me_C29St"),
#4Me_TriMe/Me_C30St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C30 aBB 20 R+S ST", "C30 aaa 20S ST", "C30 aaa 20R ST") , "4Me_TriMe/Me_C30St"),
#4Me_TriMe/Me_allSt
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "allRegst") , "4Me_TriMe/Me_allSt"),
#4Mes/all
ratio_peaks(., "4Me_TriMe", "allSteranes", "4Me/allSt"),
#Dino/all
ratio_peaks(., "allDiacholestane", c("allSteranes", "allRegHO"), "Dino/all"),
#C26-30St/C26-C30St+regHo
ratio_peaks(., c("allRegst"), c("allRegst", "Ts C27 HO", "Tm C27 HO", "C27 17B HO", "29, 30 C28 bisnor HO", "28, 30 C28 bisnor HO", "C29 Ts HO", "C29 Ba HO", "C29 BB Ho", "C30 aB HO", "C30 BB HO", "C30H Ba HO", "C31 HR Ba HO", "C31 aB HR HO", "C31 aB HS HO", "C31 BB HO", "C32 aB HS HO", "C32 aB HR HO", "C33 aB HS HO", "C33 aB HR HO", "C34 aB HR HO", "C34 aB HS HO", "C35 aB HR HO", "C35 aB HS HO"), "C26-30St/C26-C30St_regHo"),
#C27-C30aaaSt/C27-C30aaaSt+regHo
ratio_peaks(., c( "C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "allRegHO"), "C27-C30aaaSt/C27-C30aaaSt+regHo"),
#Ho/St
ratio_peaks(., "allRegHO", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "Ho/St"),
#Ho/St%
ratio_peaks(., "allRegHO", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "allRegHO" ), "Ho/St%"),
#C31_2MHI
ratio_peaks(., "C31 2a Me Ho", c("C30 aB HO", "C31 2a Me Ho" ), "C31_2MHI"),
#C31_35_2MHI
ratio_peaks(., c("C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), c("C30 aB HO", "C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), "C31_35_2MHI"),
#C31_2-MHI/C27-C30Steranes
ratio_peaks(., "C31 2a Me Ho", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST" ,"C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "C31 2a Me Ho" ), "C31_2-MHI/C27-C30Steranes"),
#MeHo/allHo
ratio_peaks(., c("C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO", "C31 3B Me HO", "C32 3B Me S HO", "C32 3B Me R HO", "C32 3B Me Ba 22S+R ST", "C33 3BMe S HO", "C33 3BMe R HO", "C34 3B Me S Ho", "C34 3B Me R HO", "C35 3B Me R HO", "C35 3B Me S HO", "C36 3B Me S HO", "C36 3B Me R HO" ), "allRegHO", "MeHo/allHo"),
#Thermal Maturity
#C27_Dia/Reg
ratio_peaks(., "C27Dia", "C27Reg", "C27Dia/Reg"),
#C27Dia_S/R
ratio_peaks(., "C27 aB 20S ST", "C27 aB 20R ST", "C27Dia_S/R"),
#C27Dia_S/S+R
ratio_peaks(., "C27 aB 20S ST", c("C27 aB 20S ST", "C27 aB 20R ST"), "C27Dia_S/S+R") ,
#C27Reg_abb/all
ratio_peaks(., c("C27 aBB 20R ST", "C27 aBB 20S ST"), c("C27 aaa 20R ST", "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST"), "C27Reg_abb/aaa"),
#C27RegaaaS/S+R
ratio_peaks(., "C27 aaa 20S ST", c("C27 aaa 20R ST", "C27 aaa 20S ST"), "C27Regaaa_S/S+R"),
#C27RegabbS/S+R
ratio_peaks(., "C27 aBB 20S ST", c("C27 aBB 20S ST", "C27 aBB 20R ST"), "C27Regabb_S/S+R"),
#C28Dia/all
ratio_peaks(., c("C28 Ba 20S ST", "C28 Ba 20R ST"), c("C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C28 Ba 20S ST", "C28 Ba 20R ST"), "C28Dia/all"),
#C28DiaS/S+R
ratio_peaks(., "C28 Ba 20S ST", c("C28 Ba 20S ST", "C28 Ba 20R ST"), "C28DiaS/S+R"),
#C28abb/all
ratio_peaks(., c("C28 aBB 20S ST", "C28 aBB 20R ST"), c("C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST"), "C28abb/all"),
#C28aaaS/S+R
ratio_peaks(., "C28 aaa 20S ST", c("C28 aaa 20S ST", "C28 aaa 20R ST"), "C28aaaS/S+R"),
#C28abbS/S+R
ratio_peaks(., "C28 aBB 20S ST", c("C28 aBB 20S ST", "C28 aBB 20R ST"), "C28abbS/S+R"),
#C29Dia/all
ratio_peaks(., c("C29 Ba 20S ST", "C29 Ba 20R ST"), c("C29 Ba 20S ST", "C29 Ba 20R ST", "C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST"), "C29Dia/all"),
#C29DiaS/S+R
ratio_peaks(., "C29 Ba 20S ST", c("C29 Ba 20S ST", "C29 Ba 20R ST"), "C29DiaS/S+R"),
#C29abb/all
ratio_peaks(., c("C29 aBB 20S ST", "C29 aBB 20R ST"), c( "C29 aaa 20S ST", "C29 aaa 20R ST", "C29 aBB 20S ST", "C29 aBB 20R ST" ), "C29abb/all"),
#C29aaaS/S+R
ratio_peaks(., "C29 aaa 20S ST", c("C29 aaa 20S ST", "C29 aaa 20R ST") , "C29aaaS/S+R"),
#C29abbS/S+R
ratio_peaks(., "C29 aBB 20S ST", c("C29 aBB 20S ST", "C29 aBB 20R ST"), "C29abbS/S+R"),
#C27Ts/Ts+Tm
ratio_peaks(., "Ts C27 HO", c("Ts C27 HO", "Tm C27 HO"), "C27Ts/Tm"),
#C28BNH29,30/28,30
ratio_peaks(., "29, 30 C28 bisnor HO", c("29, 30 C28 bisnor HO", "28, 30 C28 bisnor HO"), "C28BNH29,30/28,30"),
#C29Ts/Ts+ab
ratio_peaks(., "C29 Ts HO", c( "C29 aB HO", "C29 Ts HO"), "C29Ts/ab"),
#C29ba/ba+ab
ratio_peaks(.,"C29 Ba HO", c("C29 aB HO", "C29 Ba HO"), "C29ba/ab"),
#C29bb/bb+ab
ratio_peaks(., "C29 BB Ho", c("C29 BB Ho", "C29 aB HO"), "C29bb/ab"),
#C30_30nor/30nor+ab
ratio_peaks(., "30-nor C30H HO", c("C30 aB HO", "30-nor C30H HO"), "C30_30nor/ab"),
#C30ba/ba+ab
ratio_peaks(., "C30H Ba HO", c("C30 aB HO", "C30H Ba HO"), "C30ba/ab"),
#C31ba/ba+ab
ratio_peaks(., "C31 Ba HR HO", c("C31 aB HR HO", "C31 Ba HR HO"), "C31ba/ab"),
#C30bb/bb+ab
ratio_peaks(., "C30 BB HO", c("C30 aB HO", "C30 BB HO"), "C30bb/ab"),
#C31S/S+R
ratio_peaks(., "C31 aB HS HO", c("C31 aB HR HO", "C31 aB HS HO"), "C31S/S+R"),
#C32S/S+R
ratio_peaks(., "C32 aB HS HO", c("C32 aB HS HO", "C32 aB HR HO"), "C32S/S+R"),
#C33S/S+R
ratio_peaks(., "C33 aB HS HO", c("C33 aB HS HO", "C33 aB HR HO"), "C33S/S+R"),
#C34S/S+R
ratio_peaks(., "C34 aB HS HO", c("C34 aB HS HO", "C34 aB HR HO") , "C34S/S+R"),
#C35S/S+R
ratio_peaks(., "C35 aB HS HO", c("C35 aB HS HO", "C35 aB HR HO") , "C35S/S+R")
) }) %>% ungroup()
final_data
aromatic_final_data <- read.csv("Aromatic_SRM_SH1") %>% select( `depth`, `conc_rock.ug_g`, `peak_name`)
aliphatic_final_data <- final_data %>% select( `depth`, `conc_rock.ug_g`, `ratio`, `peak_name`)
SRM_all1 <- full_join(aromatic_final_data, aliphatic_final_data)
## Joining, by = c("depth", "conc_rock.ug_g", "peak_name")
## Warning: Column `peak_name` joining factor and character vector, coercing
## into character vector
ratio_peaks <- function(df, filter_top, filter_bottom, new_peak_name) {
filter_top <- sprintf("(%s)", str_c(filter_top, collapse = "|"))
filter_bottom <- sprintf("(%s)", str_c(filter_bottom, collapse = "|"))
filter(df, str_detect(peak_name, filter_top) | str_detect(peak_name, filter_bottom)) %>%
summarize(
depth = depth[1],
ratio2 = sum(conc_rock.ug_g[str_detect(peak_name, filter_top)]) / sum(conc_rock.ug_g[str_detect(peak_name, filter_bottom)])
) %>%
mutate(peak_name = new_peak_name)
}
SRM_all2 <- SRM_all1 %>%
group_by(depth) %>%
do({
bind_rows(.,
ratio_peaks(., "Isorenieretane", "C30 aB HO", "Iso/C30HO"),
ratio_peaks(., "Chlorobactane" , "C30 aB HO", "Chloro/C30HO"),
ratio_peaks(., "all_PAH", "C30 aB HO", "PAH/C30HO")
) }) %>% ungroup()
SRM_all <- SRM_all2 %>% select(depth, value = ratio, ratio2, conc_rock.ug_g, var = peak_name)
rock_depth <- depth_and_rock_info %>% select(depth, rock.g)
SRM_all_depth <- left_join(SRM_all, rock_depth, by = "depth")
alkane <- read_excel(file.path("metadata", "nalk_comp.xlsx")) %>% rename(depth = `meters`) %>% gather(var, value, `CPI`, `Pr/Ph`, `ACL-long`, `ACL-short`, `ACL-all`, `ngSCA/g rock`, `ngPr+Ph/g rock`, `ngLCA/g rock`, `LCA/SCA+LCA`, `SCA/LCA`)
all_data <- full_join(SRM_all_depth, alkane)
## Joining, by = c("depth", "value", "var")
osisotope <- read_excel(file.path("metadata", "SH1_Osi_forGarrett.xlsx")) %>%
rename(depth = `Depth (m)`)
cisotope <- read_excel(file.path("metadata", "Appendix_Table1_geochemistry.xlsx")) %>%
#rename columns
rename(depth = `Abs. depth (m)` , d13c_org = `Average δ13Corg (‰ VPDB)` , carb = `%Carbonate`, TOC = `%TOC`, d13c_carb = `Average δ13Ccarb (‰ VPDB)`) %>%
#remove columns not of interest
select(-`stdev δ13Corg`, -`δ13Ccarb stdev`, -`d18O-avg`, -`d18O stdev`, -`∆13C`, -`d13c_carb`)
# combine data frames
inorg_data <- bind_rows(
cisotope %>% gather(var, value, d13c_org, carb, TOC),
osisotope %>% gather(var, value, Osi)
) %>% select(depth, var, value)
all_data <- full_join(inorg_data, all_data)
## Joining, by = c("depth", "var", "value")
# show TOC - depth for interpolation
TOCscale <- cisotope %>% select(TOC, depth) %>% arrange(depth)
# provide depths to interpolate to (my data)
extrapolated_TOC <-
data_frame(
depth = all_data$depth %>% unique()
) %>%
filter(!is.na(depth)) %>%
# interpolate by mapping TOC on slope to depth, then apply my depths to that slope
mutate(
#in_range = depth <= max(TOCscale$depth) & depth >= min(TOCscale$depth),
TOC = map_dbl(depth, function(d) {
fit_data <- mutate(TOCscale, closest = abs(d - depth)) %>% arrange(closest)
m <- lm(TOC ~ depth, fit_data[1:2,])
p <- predict(m, data.frame(depth = d), se.fit = TRUE)
return(p$fit)
})
)
ggplot() +
aes(depth, TOC) +
geom_line(data = TOCscale) +
geom_point(data = extrapolated_TOC)
alldata_w_TOC <- left_join(all_data, extrapolated_TOC, by = "depth")
alldata_n_TOC2 <-
alldata_w_TOC %>%
group_by(depth) %>%
mutate(
#return values to amount for normalization
amount.ug = conc_rock.ug_g * rock.g
)%>% ungroup() %>%
arrange(depth, var)
alldata_n_TOC3 <- alldata_n_TOC2 %>% group_by(depth) %>%
mutate(
conc_TOC = amount.ug / TOC
)%>% ungroup() %>%
arrange(depth, var)
timescale <- read_excel(file.path("metadata", "Appendix_Table2_SH1_agemodel.xlsx")) %>%
rename(depth = Depth) %>%
arrange(depth)
# extrapolation
extrapolated_timescale <-
data_frame(
depth = alldata_n_TOC3$depth %>% unique()
) %>%
filter(!is.na(depth)) %>%
mutate(
in_range = depth <= max(timescale$depth) & depth >= min(timescale$depth),
ka = map_dbl(depth, function(d) {
fit_data <- mutate(timescale, closest = abs(d - depth)) %>% arrange(closest)
m <- lm(ka ~ depth, fit_data[1:10,])
p <- predict(m, data.frame(depth = d), se.fit = TRUE)
return(p$fit)
})
)
ggplot() +
aes(depth, ka) +
geom_line(data = timescale) +
geom_point(data = extrapolated_timescale, mapping = aes(color = in_range))
alldata_w_time <- left_join(alldata_n_TOC3, extrapolated_timescale, by = "depth")
d13c <- subset(alldata_w_time, var == "d13c_org") %>%
ggplot() +
geom_line() +
aes(x = ka, y = value) +
#facet_grid(~var, scales = "free")+
#scale_x_reverse() +
scale_y_continuous() +
coord_flip()
ggplotly(d13c)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
normCarot <- subset(alldata_w_time, var %in% c( "Iso/C30HO", "Chloro/C30HO")) %>%
ggplot()+
aes(ka, ratio2, color = var)+
geom_point() +
#geom_line() +
facet_grid(~var, scales = "free")+
coord_flip()
normPAH <- subset(alldata_w_time, var == "PAH/C30HO") %>%
ggplot()+
aes(ka, ratio2, color = var)+
geom_point() +
#geom_line() +
facet_grid(~var, scales = "free")+
coord_flip()
ggplotly(normPAH)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
plant <- subset(alldata_w_time, var %in% c( "ACL-long", "OleananeIndex")) %>%
ggplot()+
aes(ka, value, color = var)+
geom_point() +
#geom_line() +
facet_grid(~var, scales = "free")+
coord_flip()
ggplotly(plant)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
PAH <- subset(alldata_w_time, var %in% c( "all_PAH", "4ring_all", "5ring_all", "6ring_all", "3ring_all", "2ring_all")) %>%
ggplot()+
aes(ka, conc_TOC, color = var)+
geom_point() +
#geom_line() +
facet_grid(~var, scales = "free")+
coord_flip()
ggplotly(PAH)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
grid.arrange(PAH, plant, normPAH, ncol = 3)
## Warning: Removed 90 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 1 rows containing missing values (geom_point).
alk <- subset(alldata_w_time, var %in% c( "ACL-long", "LCA/SCA+LCA", "ngSCA/g rock", "ngLCA/g rock")) %>%
ggplot()+
aes(ka, value, color = var)+
geom_point() +
geom_line() +
facet_grid(~var, scales = "free")+
coord_flip()
ggplotly(alk)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
terr <- subset(alldata_w_time, var %in% c( "C19/C19+23" , "OleananeIndex", "C29ab/allHoab", "C24tet/tricyclics", "Ho/St", "C29St/allSt")) %>%
ggplot() +
aes(x = ka, y = value, color = var) +
geom_point() +
#geom_line() +
facet_grid(~var, scales = "free") +
#scale_x_reverse() +
coord_flip()
ggplotly(terr)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
sterane_ratios <- subset(alldata_w_time, var %in% c("C26St/allSt", "C27St/allSt", "C28St/allSt", "C30St/allSt", "C30Me/allSt", "DinoSt/allSt")) %>%
ggplot() +
aes(x = ka, y = value, color = var) +
#facet_grid(~var, scales = "free") +
geom_point() +
geom_line() +
coord_flip() +
#scale_x_reverse() +
scale_y_continuous()
ggplotly(sterane_ratios)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
tri <- subset(alldata_w_time, var %in% c("C19/tricyclics" , "C20/tricyclics" , "C21/tricyclics" , "C22/tricyclics" , "C23/tricyclics" , "C24/tricyclics" , "C25/tricyclics" , "C26/tricyclics")) %>%
ggplot() +
geom_area(mapping = aes(fill = var)) +
aes(x = ka, y = value, color = var) +
#facet_wrap(~peak_name, scales = "free") +
#scale_x_reverse() +
coord_flip()
ggplotly(tri)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
## Warning: Removed 136 rows containing missing values (position_stack).
holine <- subset(alldata_w_time, var %in% c("C30ab/allHoab", "C31ab/allHoab", "C32ab/allHoab", "C33ab/allHoab", "C34ab/allHoab", "C35ab/allHoab")) %>%
ggplot() +
#geom_area(mapping = aes(fill = var)) +
aes(x = ka, y = value, color = var) +
geom_point()+
geom_line()+
#facet_wrap(~peak_name, scales = "free") +
coord_flip() +
#scale_x_reverse() +
scale_y_continuous()
ggplotly(holine)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
HHIGI <- subset(alldata_w_time, var %in% c("HHI", "C31_2MHI", "C31 3-MHI", "GI")) %>%
ggplot() +
aes(x = ka, y = value, color = var) +
geom_point() +
geom_line() +
facet_grid(~var, scales = "free") +
#scale_x_reverse() +
coord_flip()
Carot <- subset(alldata_w_time, var %in% c("Chlorobactane", "Isorenieretane")) %>%
ggplot() +
aes(x = ka, y = conc_TOC, color = var) +
geom_point() +
geom_line() +
facet_grid(~var, scales = "free") +
#scale_x_reverse() +
coord_flip()
grid.arrange(HHIGI, normCarot, ncol = 2)
## Warning: Removed 85 rows containing missing values (geom_point).
## Warning: Removed 85 rows containing missing values (geom_path).
## Warning: Removed 2 rows containing missing values (geom_point).
srho <- alldata_w_time %>%
filter(var %in% c("C31S/S+R", "C32S/S+R", "C33S/S+R", "C34S/S+R", "C35S/S+R")) %>%
filter(value > 0.1) %>%
ggplot() +
aes(x = depth, y = value, color = var) +
geom_point() +
geom_line() +
#facet_grid(~peak_name) +
scale_x_reverse() +
coord_flip()
ggplotly(srho)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
aaa<- alldata_w_time %>%
filter(var %in% c("C27Regaaa_S/S+R", "C28aaaS/S+R", "C29aaaS/S+R")) %>%
filter(depth != 115.885) %>%
ggplot() +
aes(x = depth, y = value, color = var) +
geom_line() +
geom_point() +
facet_grid(~var, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(aaa)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
diasr <- subset(alldata_w_time, var%in% c("C28DiaS/S+R" , "C29DiaS/S+R", "C28Dia/all", "C29Dia/all")) %>%
filter(depth != 116.490) %>% filter(depth != 116.900) %>%
ggplot() +
aes(x = depth, y = value, color = var) +
geom_point() +
geom_line() +
facet_grid(~var, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(diasr)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
tstm <- subset(alldata_w_time, var %in% c("C27Ts/Tm", "C29Ts/ab")) %>%
filter(depth != 115.885) %>% filter(depth != 120.405) %>%
ggplot() +
aes(x = depth, y = value, color = var) +
geom_point() +
geom_line() +
facet_wrap(~var, scales = "free") +
scale_x_reverse() +
coord_flip()
#ggplotly(tstm)
baab <- subset(alldata_w_time, var %in% c("C29ba/ab", "C30ba/ab")) %>%
ggplot() +
aes(x = depth, y = value, color = var) +
geom_point() +
geom_line() +
facet_wrap(~var, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(baab)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
grid.arrange(aaa, srho, baab, tstm, diasr, ncol = 5)
## Warning: Removed 34 rows containing missing values (geom_point).
## Warning: Removed 34 rows containing missing values (geom_path).
TMalk<- alldata_w_time %>%
filter(var %in% c( "CPI", "Pr/Ph", "C31S/S+R", "C32S/S+R", "C29aaaS/S+R","C27Ts/Tm", "C29DiaS/S+R", "C29Dia/all", "C30ba/ab")) %>%
#filter(depth != 115.885) %>%
ggplot() +
aes(x = depth, y = value, color = var) +
geom_line() +
geom_point() +
facet_grid(~var, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(TMalk)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
erry <- alldata_w_time %>%
filter(var %in% c("allRegHO", "allRegst", "everything", "allDiacholestane", "all_tricyclics", "4Me_TriMe", "C30 aB HO")) %>%
ggplot() +
aes(x = depth, y = conc_TOC) +
geom_point() +
geom_line() +
facet_grid(~var, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(erry)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`